2,077+ academic papers on AI security, attacks, and defenses
Showing 221–240 of 986 papers
Clear filtersEnrico Ahlers, Daniel Passon, Yannic Noller +1 more
Machine learning models are increasingly present in our everyday lives; as a result, they become targets of adversarial attackers seeking to...
Yuxin Cao, Wei Song, Shangzhi Xu +2 more
Video Large Language Models (VideoLLMs) have recently achieved strong performance in video understanding tasks. However, we identify a previously...
Zijing Xu, Ziwei Ning, Tiancheng Hu +4 more
The rapid evolution of cyber threats has highlighted significant gaps in security knowledge integration. Cybersecurity Knowledge Graphs (CKGs)...
Viet Hoang Luu, Amirmohammad Pasdar, Wachiraphan Charoenwet +3 more
Modern fuzzers scale to large, real-world software but often fail to exercise the program states developers consider most fragile or...
Mohan Rajagopalan, Vinay Rao
Large Language Model (LLM) applications are vulnerable to prompt injection and context manipulation attacks that traditional security models cannot...
Ashwath Vaithinathan Aravindan, Mayank Kejriwal
Chain-of-Thought (CoT) prompting has emerged as a foundational technique for eliciting reasoning from Large Language Models (LLMs), yet the...
Weichen Yu, Ravi Mangal, Yinyi Luo +4 more
Large Language Models are rapidly becoming core components of modern software development workflows, yet ensuring code security remains challenging....
Kun Wang, Zherui Li, Zhenhong Zhou +8 more
Omni-modal Large Language Models (OLLMs) greatly expand LLMs' multimodal capabilities but also introduce cross-modal safety risks. However, a...
Zhenyu Xu, Victor S. Sheng
Protecting the intellectual property of large language models (LLMs) is a critical challenge due to the proliferation of unauthorized derivative...
Herman Errico
As artificial intelligence systems evolve from passive assistants into autonomous agents capable of executing consequential actions, the security...
Yuting Ning, Jaylen Jones, Zhehao Zhang +5 more
Computer-use agents (CUAs) have made tremendous progress in the past year, yet they still frequently produce misaligned actions that deviate from the...
Oliver Daniels, Perusha Moodley, Benjamin M. Marlin +1 more
Alignment audits aim to robustly identify hidden goals from strategic, situationally aware misaligned models. Despite this threat model, existing...
Yu Fu, Haz Sameen Shahgir, Huanli Gong +3 more
Large language models (LLMs) increasingly combine long-context processing with advanced reasoning, enabling them to retrieve and synthesize...
Yukun Jiang, Hai Huang, Mingjie Li +3 more
By introducing routers to selectively activate experts in Transformer layers, the mixture-of-experts (MoE) architecture significantly reduces...
Igor Santos-Grueiro
Safety evaluation for advanced AI systems assumes that behavior observed under evaluation predicts behavior in deployment. This assumption weakens...
Pouria Arefijamal, Mahdi Ahmadlou, Bardia Safaei +1 more
Federated learning (FL) is a decentralized learning paradigm widely adopted in resource-constrained Internet of Things (IoT) environments. These...
Benjamin Livshits
We argue that when it comes to producing secure code with AI, the prevailing "fighting fire with fire" approach -- using probabilistic AI-based...
Liwen Wang, Zongjie Li, Yuchong Xie +4 more
The evolution of Large Language Models (LLMs) into agentic systems that perform autonomous reasoning and tool use has created significant...
Shadman Rabby, Md. Hefzul Hossain Papon, Sabbir Ahmed +3 more
Sycophancy in Vision-Language Models (VLMs) refers to their tendency to align with user opinions, often at the expense of moral or factual accuracy....
Shayan Ali Hassan, Tao Ni, Zafar Ayyub Qazi +1 more
Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and generation. However, these...
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